Reference:Reference-029781: Difference between revisions

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|DOIentry=10.5194/nhess-23-3863-2023
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|BibType=journalArticle
|Title=Multivariate regression trees as an “explainable machine learning” approach to explore relationships between hydroclimatic characteristics and agricultural and hydrological drought severity: case of study Cesar River basin
|Year=2023-12-18
|Journal=Natural Hazards and Earth System Sciences
|Booktitle=None
|Volume=23
|Pages=3863–3883
|URL=https://nhess.copernicus.org/articles/23/3863/2023/
|DOI=10.5194/nhess-23-3863-2023
|Note=Auto downloaded ref at: 2024-09-07
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Revision as of 19:34, 7 September 2024



Author(s) Paez-Trujilo, Ana; Cañon, Jeffer; Hernandez, Beatriz; Corzo, Gerald; Solomatine, Dimitri;
BibType journalArticle
Title Multivariate regression trees as an “explainable machine learning” approach to explore relationships between hydroclimatic characteristics and agricultural and hydrological drought severity: case of study Cesar River basin
Editors
Year 2023-12-18
Journal Natural Hazards and Earth System Sciences
Booktitle None
Volume 23
Pages 3863–3883
URL https://nhess.copernicus.org/articles/23/3863/2023/
DOI 10.5194/nhess-23-3863-2023
ISBN
Note Auto downloaded ref at: 2024-09-07


 
Feature reference No
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MS_PublicationClusterID 0
Semantic_ID e76c972310a593c98aa25b8b74385594fd7525a9
Nr of citations 0
Sort of publication a module application description
Sort of model publication a single module
Is the CSDMS HPC used No
If HPC is used, for what project was it?:
Associated simulation movie if any:


Model(s) discussed: SWAT